In order to stably operate a system, it is important to monitor the operating status of the system and detect a sign of failure. In order to improve the accuracy of failure sign detection, it is necessary to finely set the granularity of monitoring items (increase monitoring items), but there is a dilemma in that the monitoring items need to be reduced in order to suppress the system load resulting from the acquisition of information required for the failure sign detection and the computational effort required for such failure sign detection. In response to this kind of dilemma, conventionally, measures such as refining the granularity of monitoring items and subsequently narrowing down the monitoring items to important processes or processes that may cause a failure were taken.
In order to improve the accuracy of failure sign detection, while it is ideal to narrow down the monitoring items to optimal monitoring items in accordance with the system configuration, when the configuration frequently changes as in a cloud environment, it is difficult to manually narrow down the monitoring items each time the configuration is changed, and measures for dealing with this problem are being emphasized.
Note that PTL 1 discloses a method of automatically generating monitoring items by pre-defining rules of generating monitoring items, and applying rules to each monitoring target device.